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基于熵权TOPSIS的深圳未来医疗和养老保障问题的评价及对策

Evaluation and Countermeasures of Future Medical and Pension Security Problems in Shenzhen Based on Entropy Weight and TOPSIS
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摘要 本文从人口数量与结构、经济收入与消费水平、医疗资源与水平、社会保障制度与能力五个方面出发,建立未来深圳市医疗和养老资源合理配置的评价体系。首先对原始数据标准化,借助于Matlab软件编程对16个指标进行R-型聚类,根据聚类图可以分为7类,进而选取7个指标构建评价体系。然后通过分析深圳市近十几年的各项数据,采用熵权法确定医疗和养老资源评价体系的系数。通过TOPSIS法确定评价系统的正、负理想,从而计算评价系统与理想解之间的欧氏距离,进而确定人口数量与结构、经济收入与消费水平、医疗资源与水平、社会保障制度与能力以及综合能力的排序。最后利用多元线性回归模型对人均预期寿命进行预测,进而得到人均预期寿命的回归方程。 In this paper, from the population and structure, economic income and consumption level, medical resources and level, social security system and ability of five aspects, we established the future rational allocation of medical and pension resources in Shenzhen evaluation system. Firstly, the original data were standardized, and the R-type clustering was carried out on the 16 indicators with the help of MATLAB software programming. According to the clustering diagram, the indicators could be divided into 7 categories. Then 7 indexes were selected to construct the evaluation system. Then, by analyzing the data of Shenzhen in recent ten years, the entropy weight method was adopted to determine the coefficient of the medical and pension resource evaluation system. The positive and negative ideals of the evaluation system were determined by TOPSIS method, so as to calculate the Euclidean distance between the evaluation system and the ideal solution, and then determine the order of population size and structure, economic income and consumption level, medical resources and level, social security system and ability and comprehensive ability. Finally, multiple linear regression model was used to predict the average life expectancy, and the regression equation of the average life expectancy was obtained.
出处 《应用数学进展》 2021年第2期603-616,共14页 Advances in Applied Mathematics
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